Surface water resources in arid regions are increasingly vulnerable to climate variability and growing demand, which calls for accurate, timely, and spatially explicitly monitoring approaches. This study developed a machine learning-based framework for quantifying seasonal and interannual surface water dynamics through multi-sensor fusion approach by combining radar and optical data. Sentinel-1 synthetic aperture radar (SAR), Sentinel-2 multispectral imagery, and Landsat-8 surface reflectance data were processed within the Google Earth Engine (GEE) platform for the period 2015-2021. The study used Random Forest (RF) and Gradient Tree Boosting (GTB) classifier, achieving a remarkable overall classification accuracy from Sentinel-1/2 (OA = 99.34-99.92%; Kappa = 0.8862-0.9983) and Landsat-8 (OA = 99.33-99.76%; Kappa = 0.9859-0.9949). Moreover, positive correlations were observed among water indices, particularly Modified Normalized Difference Water Index (MNDWI) and Normalized Difference Water Index (NDWI), whereas SAR backscatter variables (VV_median and VH_median) indicated a positive correlation with vegetation indices such as Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). Meanwhile, Shapley Additive Explanations (SHAP) revealed that the MNDWI, NDWI, and SAR backscatter metrics were the most influential predictors of surface water occurrence, followed by vegetation indices and lastly single bands (B2-B8). Seasonal analyses presented greater surface water variability in October and November compared to drier months of May to September. Interannual variability analysis was conducted, indicating maximum surface water extent in 2016 (28,869 km2), and minimum in 2019 (9743 km2). Meanwhile, descriptive analysis with hydroclimatic variables showed that variations in precipitation and evapotranspiration (ET) corresponded with observed spatiotemporal patterns of surface water extent except in 2017. Overall, the proposed framework offers a scalable approach for monitoring surface water variability in data-scarce arid regions, supporting water resource management, drought monitoring, and climate adaptation.
LBC Spring is a representative karst groundwater discharge system in southwestern China, characterized by elevated spring temperatures. In this paper, hydrochemical analyses and high-density temperature–depth measurements were combined to investigate the coupling between groundwater chemistry and thermal behavior in a karst geothermal system. Hydrochemical results indicate that groundwater is mainly of Ca·Mg–HCO3 and Ca·Mg–SO4 types, controlled by carbonate rock weathering. As the main regional discharge point, LBC Spring gathers water from different depths, and the chemical characteristics of its outlets show significant differences. Compared with the main thermal outlets, the cold-water outlet exhibits higher Ca2+ and lower Mg2+ concentrations, suggesting shallower circulation and shorter water–rock interaction. Gibbs diagram analysis shows that cold groundwater is dominated by rock weathering, whereas thermal groundwater is influenced by both rock weathering and evaporation–crystallization processes. Temperature–depth measurements identify multiple spring vents with stable temperature profiles under rainfall conditions, with thermal outlets exhibiting higher and stable temperatures, and cold-water outlets showing lower temperatures. The SiO2 geothermometer estimates a reservoir temperature of 45.34 °C. Mixing calculations indicate that LBC Spring represents a mixture of deep thermal water and shallow cold groundwater, with a mixing ratio of 28.1:71.9 and a circulation depth of 981–1174 m. The coupled hydrochemical–thermal analysis provides robust constraints on groundwater circulation and geothermal potential in karst systems.
Macrophomina phaseolina, the causal agent of charcoal rot disease, poses a major threat to Phaseolus vulgaris production, particularly under climate change. Climate-induced environmental extremes, in which elevated temperatures and drought conditions favour disease development and pathogen aggressiveness, pose a major challenge to agricultural productivity globally. This study assessed the plant growth-promoting and biocontrol potential of six bacterial endophytic isolates against M. phaseolina in P. vulgaris, using an integration of biochemical, physiological antifungal, and seed germination assays. All the isolates show significant potential (p < 0.05) for producing ammonia and indole-3-acetic acid (IAA), solubilising nutrients, exhibiting hydrolytic enzyme activity, and demonstrating biocontrol traits. Of the six isolates, Serratia marcescens (PR1AI2) showed the highest IAA production and zinc solubilization activity, whereas Enterobacter sp. L1I9 showed enhanced phosphate solubilization. Protease activity was highest in PR1AI2, while Pseudomonas rhodesiae strain MSG-15 (L3I2) exhibited the strongest amylase activity. Dual culture assays demonstrated significant inhibition (p < 0.05) of M. phaseolina mycelial growth and reduction in sporulation by the endophytic bacterial isolates. Among the isolates, L3I2 had the highest inhibition of mycelial growth (75.93%), whereas PR1AI2 qualitatively showed the greatest sporulation reduction. Seed germination assays further showed variable responses under M. phaseolina, with Streptomyces bikiniensis strain SBM (L2I3) and Enterobacter kobei strain V51 (PR5AI1) showing germination percentages of 80.00% and 75.56%, respectively, compared with 76.67% in the M. phaseolina-treated control. These isolates therefore represent promising candidates for sustainable biological management of charcoal rot disease in P. vulgaris, as they possess multiple traits associated with pathogen suppression and improved plant development.
Macroinvertebrates such as snails and crabs influence aspects of salt marsh structure and function through herbivory and bioturbation. However, the effects of physico-chemical variables and habitat composition on their abundance and distribution remain underexplored. This study examined the influence of environmental factors on snail and crab populations across salt marsh habitats in the Berg River Estuary on the west coast of South Africa, hypothesising greater abundance in the intertidal than in the supratidal zone, driven by salinity and elevation. Snail and crab abundance were assessed using manual counts in triplicate quadrats (10 & times; 10 cm for snails; 25 & times; 25 cm for crab burrows) across six transects. Physicochemical variables of sediment and groundwater were also analysed. Six snail species (Davisassiminea sp. 1, Davisassiminea sp. 2, D. capensis, D. globulus, Afrolittorina africana and Melanoides tuberculata) and one crab species (Hymenosoma orbiculare) were recorded. Crab burrow density differed significantly between habitats, with the highest abundance at creek edges (85.37 burrows m-2) and lowest in supratidal habitat (8.57 burrows m-2). Snail richness and abundance declined with elevation; Davisassiminea sp. 2 and D. capensis occurred only at creek edges. Habitat and environmental variables explained 32% of the variation in macroinvertebrate abundance, with sediment conductivity and organic content being key predictors. Generalised linear models indicated that species richness declined with increasing sediment redox potential (t = -2.25, p = 0.025), organic matter (t = -2.07, p = 0.040) and clay content (t = -3.07, p = 0.003). These findings highlight the influence of local environmental conditions in shaping and predicting species distributions under a changing climate.
Generating a cost-effective precious-metal catalyst is essential for achieving low-cost, large-scale green hydrogen production. Since the majority of the overpotential in the proton exchange membrane water electrolyzer arises during the oxygen evolution reaction (OER), the remarkable performance of the IrO2 makes it an ideal anodic catalyst. Herein, a simple, straightforward method was used to prepare an IrO2-loaded transition-metal carbide-supported catalyst. The IrO2 nanoparticles were loaded on TiC (IrxTC1-x) and Ti2AlC (Ir(x)TAC(1-x)) at 20 to 80 wt% IrO2 loadings, using the modified Adams fusion method. A diameter of 2 nm was obtained to exhibit improved OER performance in 0.5 M H2SO4 compared with commercial IrO2. The catalysts showed a uniform distribution of IrO2 nanoparticles on the supports. Overpotentials of 260 and 250 mV were obtained for Ir80TC20 and Ir(80)TAC(20) at 10 mA cm(-2). The prepared Ir80TC20 and Ir(80)TAC(20) showed good OER activity, delivering 10 mA cm(-2) at 1.47 and 1.46 V versus RHE, respectively. The catalysts exhibited OER stability at 10 mA cm(-2) for 73 and 58 h, respectively, for Ir80TC20 and Ir(80)TAC(20). The precursor solution proved significant recyclability, and the study demonstrated a new approach to rapidly design low-cost, high-performance anodic catalysts for overall OER performance.
